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Register a new userNear-Optimal Linear Precoding with Low Complexity for Massive MIMO
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Added by
Linglong Dai
Publication date
2014
fields
Informatics Engineering
and research's language is
English
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Linear precoding techniques can achieve near- optimal capacity due to the special channel property in down- link massive MIMO systems, but involve high complexity since complicated matrix inversion of large size is required. In this paper, we propose a low-complexity linear precoding scheme based on the Gauss-Seidel (GS) method. The proposed scheme can achieve the capacity-approaching performance of the classical linear precoding schemes in an iterative way without complicated matrix inversion, which can reduce the overall complexity by one order of magnitude. The performance guarantee of the proposed GS-based precoding is analyzed from the following three aspects. At first, we prove that GS-based precoding satisfies the transmit power constraint. Then, we prove that GS-based precoding enjoys a faster convergence rate than the recently proposed Neumann-based precoding. At last, the convergence rate achieved by GS-based precoding is quantified, which reveals that GS-based precoding converges faster with the increasing number of BS antennas. To further accelerate the convergence rate and reduce the complexity, we propose a zone-based initial solution to GS-based precoding, which is much closer to the final solution than the traditional initial solution. Simulation results demonstrate that the proposed scheme outperforms Neumann- based precoding, and achieves the exact capacity-approaching performance of the classical linear precoding schemes with only a small number of iterations both in Rayleigh fading channels and spatially correlated channels.
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A clustered base transceiver station (BTS) coordination strategy is proposed for a large cellular MIMO network, which includes full intra-cluster coordination to enhance the sum rate and limited inter-cluster coordination to reduce interference for the cluster edge users. Multi-cell block diagonalization is used to coordinate the transmissions across multiple BTSs in the same cluster. To satisfy per-BTS power constraints, three combined precoder and power allocation algorithms are proposed with different performance and complexity tradeoffs. For inter-cluster coordination, the coordination area is chosen to balance fairness for edge users and the achievable sum rate. It is shown that a small cluster size (about 7 cells) is sufficient to obtain most of the sum rate benefits from clustered coordination while greatly relieving channel feedback requirement. Simulations show that the proposed coordination strategy efficiently reduces interference and provides a considerable sum rate gain for cellular MIMO networks.
Benefiting from tens of GHz bandwidth, terahertz (THz) communication is considered to be a promising technology to provide ultra-high speed data rates for future 6G wireless systems. To compensate for the serious propagation attenuation of THz signals, massive multiple-input multiple-output (MIMO) with hybrid precoding can be utilized to generate directional beams with high array gains. However, the standard hybrid precoding architecture based on frequency-independent phase-shifters cannot cope with the beam split effect in THz massive MIMO systems, where the directional beams will split into different physical directions at different subcarrier frequencies. The beam split effect will result in a serious array gain loss across the entire bandwidth, which has not been well investigated in THz massive MIMO systems. In this paper, we first reveal and quantify the seriousness of the beam split effect in THz massive MIMO systems by analyzing the array gain loss it causes. Then, we propose a new precoding architecture called delay-phase precoding (DPP) to mitigate this effect. Specifically, the proposed DPP introduces a time delay network as a new precoding layer between radio-frequency chains and phase-shifters in the standard hybrid precoding architecture. In this way, conventional phase-controlled analog beamforming can be converted into delay-phase controlled analog beamforming. Unlike frequency-independent phase shifts, the time delay network introduced in the DPP can realize frequency-dependent phase shifts, which can be designed to generate frequency-dependent beams towards the target physical direction across the entire THz bandwidth. Due to the joint control of delay and phase, the proposed DPP can significantly relieve the array gain loss caused by the beam split effect. Furthermore, we propose a hardware structure by using true-time-delayers to realize the concept of DPP.
In this paper, the feasibility of a new downlink transmission mode in massive multi-input multi-output (MIMO) systems is investigated with two types of users, i.e., the users with only statistical channel state information (CSI) and the users with imperfect instantaneous CSI. The problem of downlink precoding design with mixed utilization of statistical and imperfect instantaneous CSI is addressed. We first theoretically analyze the impact of the mutual interference between the two types of users on their achievable rate. Then, considering the mutual interference suppression, we propose an extended zero-forcing (eZF) and an extended maximum ratio transmission (eMRT) precoding methods to minimize the total transmit power of base station and to maximize the received signal power of users, respectively. Thanks to the exploitation of statistical CSI, pilot-based channel estimation is avoided enabling more active users, higher system sum rate and shorter transmission delay. Finally, simulations are performed to validate the accuracy of the theoretical analysis and the advantages of the proposed precoding methods.
This paper investigates user cooperation in massive multiple-input multiple-output (MIMO) systems with cascaded precoding. The high-dimensional physical channel in massive MIMO systems can be converted into a low-dimensional effective channel through the inner precoder to reduce the overhead of channel estimation and feedback. The inner precoder depends on the spatial covariance matrix of the channels, and thus the same precoder can be used for different users as long as they have the same spatial covariance matrix. Spatial covariance matrix is determined by the surrounding environment of user terminals. Therefore, the users that are close to each other will share the same spatial covariance matrix. In this situation, it is possible to achieve user cooperation by sharing receiver information through some dedicated link, such as device-to-device communications. To reduce the amount of information that needs to be shared, we propose a decoding codebook based scheme, which can achieve user cooperation without the need of channel state information. Moreover, we also investigate the amount of bandwidth required to achieve efficient user cooperation. Simulation results show that user cooperation can improve the capacity compared to the non-cooperation scheme.
In a cooperative multiple-antenna downlink cellular network, maximization of a concave function of user rates is considered. A new linear precoding technique called soft interference nulling (SIN) is proposed, which performs at least as well as zero-forcing (ZF) beamforming. All base stations share channel state information, but each users message is only routed to those that participate in the users coordination cluster. SIN precoding is particularly useful when clusters of limited sizes overlap in the network, in which case traditional techniques such as dirty paper coding or ZF do not directly apply. The SIN precoder is computed by solving a sequence of convex optimization problems. SIN under partial network coordination can outperform ZF under full network coordination at moderate SNRs. Under overlapping coordination clusters, SIN precoding achieves considerably higher throughput compared to myopic ZF, especially when the clusters are large.
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